Artificial Intelligence empowered evolution in medicine food homology: Innovations, challenges, and future prospects

Artificial Intelligence (AI) is revolutionizing the medicine food homology (MFH) industry by enhancing cultivation, processing, and traceability, leading to greater efficiency, quality, and sustainability. This review explores the challenges in AI's application in MFH, including accurate identification, quality management, and chemical composition variability, as well as technical hurdles in function prediction. It highlights how AI technologies, integrated with data-driven models, are addressing key aspects of MFH production such as precise quality assessment, compositional analysis, and monitoring of growth environments. AI systems are improving the accuracy of MFH production identification and boosting the prediction of functional properties. The integration of AI is bringing significant advancements in quality control, sustainability, and efficiency, ensuring better yields and enhancing traceability throughout the MFH supply chain to guarantee quality and safety.